Cargando…
Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series
Next-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there are few reports about their use in clinical practice. Which patients would most profit from testing, and information on the likelihood of discovery of a ca...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330090/ https://www.ncbi.nlm.nih.gov/pubmed/30279455 http://dx.doi.org/10.1038/s41380-018-0224-0 |
_version_ | 1783386921921150976 |
---|---|
author | Koriath, C. Kenny, J. Adamson, G. Druyeh, R. Taylor, W. Beck, J. Quinn, L. Mok, T. H. Dimitriadis, A. Norsworthy, P. Bass, N. Carter, J. Walker, Z. Kipps, C. Coulthard, E. Polke, J. M. Bernal-Quiros, M. Denning, N. Thomas, R. Raybould, R. Williams, J. Mummery, C. J. Wild, E. J. Houlden, H. Tabrizi, S. J. Rossor, M. N. Hummerich, H. Warren, J. D. Rowe, J. B. Rohrer, J. D. Schott, J. M. Fox, N. C. Collinge, J. Mead, S. |
author_facet | Koriath, C. Kenny, J. Adamson, G. Druyeh, R. Taylor, W. Beck, J. Quinn, L. Mok, T. H. Dimitriadis, A. Norsworthy, P. Bass, N. Carter, J. Walker, Z. Kipps, C. Coulthard, E. Polke, J. M. Bernal-Quiros, M. Denning, N. Thomas, R. Raybould, R. Williams, J. Mummery, C. J. Wild, E. J. Houlden, H. Tabrizi, S. J. Rossor, M. N. Hummerich, H. Warren, J. D. Rowe, J. B. Rohrer, J. D. Schott, J. M. Fox, N. C. Collinge, J. Mead, S. |
author_sort | Koriath, C. |
collection | PubMed |
description | Next-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there are few reports about their use in clinical practice. Which patients would most profit from testing, and information on the likelihood of discovery of a causal variant in a clinical syndrome, are conspicuously absent from the literature, mostly for a lack of large-scale studies. We applied a validated NGS dementia panel to 3241 patients with dementia and healthy aged controls; 13,152 variants were classified by likelihood of pathogenicity. We identified 354 deleterious variants (DV, 12.6% of patients); 39 were novel DVs. Age at clinical onset, clinical syndrome and family history each strongly predict the likelihood of finding a DV, but healthcare setting and gender did not. DVs were frequently found in genes not usually associated with the clinical syndrome. Patients recruited from primary referral centres were compared with those seen at higher-level research centres and a national clinical neurogenetic laboratory; rates of discovery were comparable, making selection bias unlikely and the results generalisable to clinical practice. We estimated penetrance of DVs using large-scale online genomic population databases and found 71 with evidence of reduced penetrance. Two DVs in the same patient were found more frequently than expected. These data should provide a basis for more informed counselling and clinical decision making. |
format | Online Article Text |
id | pubmed-6330090 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-63300902019-04-02 Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series Koriath, C. Kenny, J. Adamson, G. Druyeh, R. Taylor, W. Beck, J. Quinn, L. Mok, T. H. Dimitriadis, A. Norsworthy, P. Bass, N. Carter, J. Walker, Z. Kipps, C. Coulthard, E. Polke, J. M. Bernal-Quiros, M. Denning, N. Thomas, R. Raybould, R. Williams, J. Mummery, C. J. Wild, E. J. Houlden, H. Tabrizi, S. J. Rossor, M. N. Hummerich, H. Warren, J. D. Rowe, J. B. Rohrer, J. D. Schott, J. M. Fox, N. C. Collinge, J. Mead, S. Mol Psychiatry Article Next-generation genetic sequencing (NGS) technologies facilitate the screening of multiple genes linked to neurodegenerative dementia, but there are few reports about their use in clinical practice. Which patients would most profit from testing, and information on the likelihood of discovery of a causal variant in a clinical syndrome, are conspicuously absent from the literature, mostly for a lack of large-scale studies. We applied a validated NGS dementia panel to 3241 patients with dementia and healthy aged controls; 13,152 variants were classified by likelihood of pathogenicity. We identified 354 deleterious variants (DV, 12.6% of patients); 39 were novel DVs. Age at clinical onset, clinical syndrome and family history each strongly predict the likelihood of finding a DV, but healthcare setting and gender did not. DVs were frequently found in genes not usually associated with the clinical syndrome. Patients recruited from primary referral centres were compared with those seen at higher-level research centres and a national clinical neurogenetic laboratory; rates of discovery were comparable, making selection bias unlikely and the results generalisable to clinical practice. We estimated penetrance of DVs using large-scale online genomic population databases and found 71 with evidence of reduced penetrance. Two DVs in the same patient were found more frequently than expected. These data should provide a basis for more informed counselling and clinical decision making. Nature Publishing Group UK 2018-10-02 2020 /pmc/articles/PMC6330090/ /pubmed/30279455 http://dx.doi.org/10.1038/s41380-018-0224-0 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Koriath, C. Kenny, J. Adamson, G. Druyeh, R. Taylor, W. Beck, J. Quinn, L. Mok, T. H. Dimitriadis, A. Norsworthy, P. Bass, N. Carter, J. Walker, Z. Kipps, C. Coulthard, E. Polke, J. M. Bernal-Quiros, M. Denning, N. Thomas, R. Raybould, R. Williams, J. Mummery, C. J. Wild, E. J. Houlden, H. Tabrizi, S. J. Rossor, M. N. Hummerich, H. Warren, J. D. Rowe, J. B. Rohrer, J. D. Schott, J. M. Fox, N. C. Collinge, J. Mead, S. Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title | Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title_full | Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title_fullStr | Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title_full_unstemmed | Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title_short | Predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
title_sort | predictors for a dementia gene mutation based on gene-panel next-generation sequencing of a large dementia referral series |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6330090/ https://www.ncbi.nlm.nih.gov/pubmed/30279455 http://dx.doi.org/10.1038/s41380-018-0224-0 |
work_keys_str_mv | AT koriathc predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT kennyj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT adamsong predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT druyehr predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT taylorw predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT beckj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT quinnl predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT mokth predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT dimitriadisa predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT norsworthyp predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT bassn predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT carterj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT walkerz predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT kippsc predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT coultharde predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT polkejm predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT bernalquirosm predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT denningn predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT thomasr predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT raybouldr predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT williamsj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT mummerycj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT wildej predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT houldenh predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT tabrizisj predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT rossormn predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT hummerichh predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT warrenjd predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT rowejb predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT rohrerjd predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT schottjm predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT foxnc predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT collingej predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries AT meads predictorsforadementiagenemutationbasedongenepanelnextgenerationsequencingofalargedementiareferralseries |